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toy-example

TOY EXAMPLE

This script shows a toy example of usage of SparseFunClust (without alignment).

Generate the data

library(SparseFunClust)
set.seed(24032023)
n <- 50
x <- seq(0,1,len=500)
out <- generate.data.FV17(n, x)
data <- out$data
trueClust <- out$true.partition
matplot(x, t(data), type='l', col=trueClust,
        xlab = 'x', ylab = 'data', main = 'Simulated data')

Run Sparse Functional Clustering (no alignment)

K <- 2            # run with 2 groups only
method <- 'kmea'  # version with K-means clustering
tuning.m <- FALSE # don't perform tuning of the sparsity parameter (faster)
result <- SparseFunClust(data, x, K = K, do.alignment = FALSE,
                         clust.method = method, tuning.m = tuning.m)

Plot / explore results

table(trueClust,result$labels)

##          
## trueClust  1  2
##         1 50  0
##         2 10 40

cer(trueClust,result$labels)

## [1] 0.1818182

matplot(x,t(data),type='l',lty=1,col=result$labels+1,ylab='',
        main='clustering results')
lines(x,colMeans(data[which(result$labels==1),]),lwd=2)
lines(x,colMeans(data[which(result$labels==2),]),lwd=2)

plot(x,result$w,type='l',lty=1,lwd=2,ylab='',
     main='estimated weighting function')
abline(v=0.5)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.